BackgroundOwing to its independence from the main Central European drainage systems, the Italian freshwater fauna is characterized by a high degree of endemicity. Three main ichthyogeographic districts have been proposed in Italy. Yet, the validity of these regions has not been confirmed by phylogenetic and population genetic analyses and a phylogeographic scenario for Italy's primary freshwater fish fauna is still lacking. Here, we investigate the phylogeography of the Italian vairone (Telestes muticellus).ResultsWe sampled 38 populations representing the species' entire distribution range and covering all relevant drainage systems, and genotyped 509 individuals at eight variable microsatellite loci. Applying various population genetic analyses, we identify five distinct groups of populations that are only partly in agreement with the proposed ichthyogeographic districts. Our group I, which is formed by specimens from Veneto and the Po River system draining into the Adriatic Sea, corresponds to the Padano-Venetian ichthyogeographic district (PV), except for two Middle Adriatic drainages, which we identify as a separate group (III). The Tuscano-Latium district (TL) is equivalent to our group V. A more complex picture emerges for the Ligurian drainages: populations from Central Liguria belong to group I, while populations from West (group II) and East Liguria (group IV) form their own groups, albeit with affinities to PV and TL, respectively.ConclusionsWe propose a phylogeographic scenario for T. muticellus in which an initial T. muticellus stock became isolated from the 'Alpine' clade and survived the various glaciation cycles in several refugia. These were situated in the Upper Adriatic (groups I and II), the Middle Adriatic (group III), (East) Liguria (group IV) and Tuscano-Latium (group V). The population structure in the vairone is, in principal, in agreement with the two main ichthyogeographic districts (PV and TL), except for the two populations in the Middle Adriatic, which we identify as additional major "district".
Ecotoxicological studies performed for the authorization of plant protection products (PPP) usually result in the reporting of endpoint values in terms of effect concentration (EC) affecting a percentage x of test organisms or where a x percentage of an effect is observed (EC x ). The new Regulation (EC) No. 1107/2009 for the authorization of PPPs and the related data requirements provide that ecotoxicological endpoint data from chronic or long-term studies submitted by the Applicant are reported as EC 10 or EC 20 values together with the NOEC. NOEC values have been criticized since their values strongly depends on the experimental study design, whereas EC x values take into account the whole concentration-response curve and are therefore considered more appropriate. The aim of the project is to investigate the comparability of the EC x approach to the current NOEC approach on a larger data sets in view of the new Regulation requirements. Ecotoxicological data gathered from 70 active substances' approval dossiers were collected and stored into a MS Access database. All the extracted ecotoxicological data were analyzed in order to derive NOEC and calculate EC 10 , EC 20 , EC 50 with confidence intervals, using statistical models from the exponential and Hill families for continuous data, and logistic, log-logistic and complementary log-log models for quantal data. The optimal model was selected based on likelihood ratio tests and the Akaike Information Criterion. EC x /NOEC ratio distributions were calculated considering the whole set of data and model outputs; data were grouped in different categories to remark any differences in the EC x /NOEC ratio distributions.
European Pesticide Registration requires a risk assessment (RA) for nontarget organisms according to EU Regulation. European Authorities have developed Guidance Documents (GDs) for RA considering exposure scenarios for the required organisms typical for terrestrial crops. The "Birds and Mammals EFSA GD" allows using multiple sources of information to extract information on species frequency needed in identifying focal species for higher-tier RA. We developed an analytical framework to calculate species frequency according to availability of species and habitat quantitative data. Since the exposure scenarios reported in the EFSA GD are inconsistent for rice, we tested the method on birds and mammals in a portion of the largest rice-cultivated area of Europe, the Italian Po floodplain. We derived three lists of focal species: (a) an expert-based list based on land-use data only, which can be useful for a preliminary exploration of potential candidate species; (b) a list derived from the interpolation of species data only, which reflects actual species frequency in rice fields; and (c) a list obtained by a species distribution model based on species monitoring and land-use data, which account for species selectivity for rice crops and are transferable to other contexts. Focal species were identified for crop-specific diet-foraging guilds, to build specific exposure scenarios to assess the risk from pesticides application in rice fields. The partial differences between our lists and those previously proposed highlight the need for identifying national lists, which can vary according to study area, biogeographic region and exposure scenarios. The application of the proposed method in European riceproducing countries should lead to crop-specific lists, which could then be integrated to obtain a flexible European list applicable to higher-tier RA. Integr Environ Assess Manag 2021;00:1-15.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.